RAxML-NG v. 1.0.2 released on 22.02.2021 by The Exelixis Lab.
Developed by: Alexey M. Kozlov and Alexandros Stamatakis.
Contributors: Diego Darriba, Tomas Flouri, Benoit Morel, Sarah Lutteropp, Ben Bettisworth.
Latest version: https://github.com/amkozlov/raxml-ng
Questions/problems/suggestions? Please visit: https://groups.google.com/forum/#!forum/raxml

System: Intel(R) Xeon(R) Gold 6148 CPU @ 2.40GHz, 40 cores, 376 GB RAM

RAxML-NG was called at 01-Jul-2021 15:05:51 as follows:

raxml-ng --msa /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/2_msa/Q9ULK4_trimmed_msa.fasta --data-type AA --model LG4X --prefix /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4 --seed 2 --threads 8 --tree rand{20} pars{20}

Analysis options:
  run mode: ML tree search
  start tree(s): random (20)
  random seed: 2
  tip-inner: OFF
  pattern compression: ON
  per-rate scalers: OFF
  site repeats: ON
  fast spr radius: AUTO
  spr subtree cutoff: 1.000000
  branch lengths: proportional (ML estimate, algorithm: NR-FAST)
  SIMD kernels: AVX2
  parallelization: coarse-grained (auto), PTHREADS (8 threads), thread pinning: OFF

[00:00:00] Reading alignment from file: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/2_msa/Q9ULK4_trimmed_msa.fasta
[00:00:00] Loaded alignment with 225 taxa and 1326 sites

WARNING: Sequences tr_B4QI28_B4QI28_DROSI_7240 and tr_B4I8D4_B4I8D4_DROSE_7238 are exactly identical!
WARNING: Sequences tr_Q28X42_Q28X42_DROPS_46245 and tr_B4H505_B4H505_DROPE_7234 are exactly identical!
WARNING: Sequences tr_A0A2I3RBW7_A0A2I3RBW7_PANTR_9598 and sp_Q9ULK4_MED23_HUMAN_9606 are exactly identical!
WARNING: Sequences tr_A0A2I3RBW7_A0A2I3RBW7_PANTR_9598 and tr_A0A0D9RVR8_A0A0D9RVR8_CHLSB_60711 are exactly identical!
WARNING: Sequences tr_A0A2I3RBW7_A0A2I3RBW7_PANTR_9598 and tr_A0A2K5KTV1_A0A2K5KTV1_CERAT_9531 are exactly identical!
WARNING: Sequences tr_A0A2I3RBW7_A0A2I3RBW7_PANTR_9598 and tr_A0A2K5XGR7_A0A2K5XGR7_MANLE_9568 are exactly identical!
WARNING: Sequences tr_A0A2I3RBW7_A0A2I3RBW7_PANTR_9598 and tr_A0A2R8ZHI1_A0A2R8ZHI1_PANPA_9597 are exactly identical!
WARNING: Sequences tr_A0A158NHZ3_A0A158NHZ3_ATTCE_12957 and tr_A0A195AWH8_A0A195AWH8_9HYME_520822 are exactly identical!
WARNING: Sequences tr_A0A2D0PVG5_A0A2D0PVG5_ICTPU_7998 and tr_A0A2D0PYK0_A0A2D0PYK0_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2D0PVG5_A0A2D0PVG5_ICTPU_7998 and tr_A0A2D0PZH9_A0A2D0PZH9_ICTPU_7998 are exactly identical!
WARNING: Sequences tr_A0A2U3V0P2_A0A2U3V0P2_TURTR_9739 and tr_A0A2Y9LZ89_A0A2Y9LZ89_DELLE_9749 are exactly identical!
WARNING: Sequences tr_A0A2U3V0P2_A0A2U3V0P2_TURTR_9739 and tr_A0A2Y9FEQ3_A0A2Y9FEQ3_PHYCD_9755 are exactly identical!
WARNING: Sequences tr_A0A2U3V0P2_A0A2U3V0P2_TURTR_9739 and tr_A0A384AUF5_A0A384AUF5_BALAS_310752 are exactly identical!
WARNING: Sequences tr_A0A2U3VZW9_A0A2U3VZW9_ODORO_9708 and tr_A0A2U3Y7M3_A0A2U3Y7M3_LEPWE_9713 are exactly identical!
WARNING: Duplicate sequences found: 14

NOTE: Reduced alignment (with duplicates and gap-only sites/taxa removed) 
NOTE: was saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.reduced.phy

Alignment comprises 1 partitions and 1326 patterns

Partition 0: noname
Model: LG4X+R4
Alignment sites / patterns: 1326 / 1326
Gaps: 19.37 %
Invariant sites: 1.21 %


NOTE: Binary MSA file created: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.rba

Parallelization scheme autoconfig: 1 worker(s) x 8 thread(s)

Parallel reduction/worker buffer size: 1 KB  / 0 KB

[00:00:00] Generating 20 random starting tree(s) with 225 taxa
[00:00:00] Data distribution: max. partitions/sites/weight per thread: 1 / 166 / 13280
[00:00:00] Data distribution: max. searches per worker: 20

Starting ML tree search with 20 distinct starting trees

[00:00:00 -286252.612715] Initial branch length optimization
[00:00:00 -208656.025362] Model parameter optimization (eps = 10.000000)
[00:00:11 -207739.438724] AUTODETECT spr round 1 (radius: 5)
[00:00:21 -162415.663873] AUTODETECT spr round 2 (radius: 10)
[00:00:35 -112138.278412] AUTODETECT spr round 3 (radius: 15)
[00:00:51 -97825.596166] AUTODETECT spr round 4 (radius: 20)
[00:01:10 -97075.948043] AUTODETECT spr round 5 (radius: 25)
[00:01:29 -97069.385877] SPR radius for FAST iterations: 25 (autodetect)
[00:01:29 -97069.385877] Model parameter optimization (eps = 3.000000)
[00:01:40 -96846.715158] FAST spr round 1 (radius: 25)
[00:01:57 -91717.381553] FAST spr round 2 (radius: 25)
[00:02:11 -91484.305332] FAST spr round 3 (radius: 25)
[00:02:22 -91481.780250] FAST spr round 4 (radius: 25)
[00:02:31 -91481.778797] Model parameter optimization (eps = 1.000000)
[00:02:36 -91476.652372] SLOW spr round 1 (radius: 5)
[00:02:56 -91462.807077] SLOW spr round 2 (radius: 5)
[00:03:16 -91460.669060] SLOW spr round 3 (radius: 5)
[00:03:34 -91460.668038] SLOW spr round 4 (radius: 10)
[00:03:54 -91460.667667] SLOW spr round 5 (radius: 15)
[00:04:32 -91460.667420] SLOW spr round 6 (radius: 20)
[00:05:12 -91460.667242] SLOW spr round 7 (radius: 25)
[00:05:42 -91460.667112] Model parameter optimization (eps = 0.100000)

[00:05:45] ML tree search #1, logLikelihood: -91460.588565

[00:05:45 -285265.174803] Initial branch length optimization
[00:05:45 -209610.061674] Model parameter optimization (eps = 10.000000)
[00:05:54 -208739.799826] AUTODETECT spr round 1 (radius: 5)
[00:06:04 -153864.848352] AUTODETECT spr round 2 (radius: 10)
[00:06:17 -117041.383357] AUTODETECT spr round 3 (radius: 15)
[00:06:34 -98877.230157] AUTODETECT spr round 4 (radius: 20)
[00:06:53 -98797.713078] AUTODETECT spr round 5 (radius: 25)
[00:07:12 -98797.035104] SPR radius for FAST iterations: 25 (autodetect)
[00:07:12 -98797.035104] Model parameter optimization (eps = 3.000000)
[00:07:27 -98481.841975] FAST spr round 1 (radius: 25)
[00:07:44 -91582.946765] FAST spr round 2 (radius: 25)
[00:07:58 -91496.358536] FAST spr round 3 (radius: 25)
[00:08:10 -91475.703180] FAST spr round 4 (radius: 25)
[00:08:19 -91475.702068] Model parameter optimization (eps = 1.000000)
[00:08:23 -91473.919331] SLOW spr round 1 (radius: 5)
[00:08:42 -91464.299431] SLOW spr round 2 (radius: 5)
[00:09:00 -91464.297736] SLOW spr round 3 (radius: 10)
[00:09:20 -91464.111372] SLOW spr round 4 (radius: 5)
[00:09:46 -91463.799014] SLOW spr round 5 (radius: 5)
[00:10:09 -91463.795085] SLOW spr round 6 (radius: 10)
[00:10:32 -91463.792433] SLOW spr round 7 (radius: 15)
[00:11:11 -91463.790642] SLOW spr round 8 (radius: 20)
[00:11:49 -91463.789435] SLOW spr round 9 (radius: 25)
[00:12:23 -91463.788625] Model parameter optimization (eps = 0.100000)

[00:12:25] ML tree search #2, logLikelihood: -91463.741076

[00:12:25 -292290.628203] Initial branch length optimization
[00:12:26 -207706.136980] Model parameter optimization (eps = 10.000000)
[00:12:37 -206808.093912] AUTODETECT spr round 1 (radius: 5)
[00:12:47 -153433.749634] AUTODETECT spr round 2 (radius: 10)
[00:13:01 -123792.191904] AUTODETECT spr round 3 (radius: 15)
[00:13:17 -106121.369506] AUTODETECT spr round 4 (radius: 20)
[00:13:33 -102327.013578] AUTODETECT spr round 5 (radius: 25)
[00:13:47 -102326.979415] SPR radius for FAST iterations: 20 (autodetect)
[00:13:47 -102326.979415] Model parameter optimization (eps = 3.000000)
[00:13:58 -101978.118130] FAST spr round 1 (radius: 20)
[00:14:16 -91715.660027] FAST spr round 2 (radius: 20)
[00:14:31 -91490.404090] FAST spr round 3 (radius: 20)
[00:14:41 -91487.772658] FAST spr round 4 (radius: 20)
[00:14:50 -91487.766724] Model parameter optimization (eps = 1.000000)
[00:14:57 -91478.954785] SLOW spr round 1 (radius: 5)
[00:15:17 -91460.623027] SLOW spr round 2 (radius: 5)
[00:15:36 -91458.535081] SLOW spr round 3 (radius: 5)
[00:15:54 -91458.534032] SLOW spr round 4 (radius: 10)
[00:16:14 -91458.533655] SLOW spr round 5 (radius: 15)
[00:16:52 -91458.533409] SLOW spr round 6 (radius: 20)
[00:17:31 -91458.533214] SLOW spr round 7 (radius: 25)
[00:18:01 -91458.533127] Model parameter optimization (eps = 0.100000)

[00:18:04] ML tree search #3, logLikelihood: -91458.458172

[00:18:04 -288638.500159] Initial branch length optimization
[00:18:04 -208862.769584] Model parameter optimization (eps = 10.000000)
[00:18:21 -207930.820401] AUTODETECT spr round 1 (radius: 5)
[00:18:30 -162275.221435] AUTODETECT spr round 2 (radius: 10)
[00:18:44 -123843.658555] AUTODETECT spr round 3 (radius: 15)
[00:18:59 -102271.991947] AUTODETECT spr round 4 (radius: 20)
[00:19:19 -99423.087653] AUTODETECT spr round 5 (radius: 25)
[00:19:38 -99423.038436] SPR radius for FAST iterations: 20 (autodetect)
[00:19:38 -99423.038436] Model parameter optimization (eps = 3.000000)
[00:19:49 -99143.882292] FAST spr round 1 (radius: 20)
[00:20:08 -92122.806338] FAST spr round 2 (radius: 20)
[00:20:23 -91499.204099] FAST spr round 3 (radius: 20)
[00:20:36 -91477.237282] FAST spr round 4 (radius: 20)
[00:20:46 -91476.994817] FAST spr round 5 (radius: 20)
[00:20:55 -91476.931897] Model parameter optimization (eps = 1.000000)
[00:21:00 -91472.849319] SLOW spr round 1 (radius: 5)
[00:21:21 -91461.313712] SLOW spr round 2 (radius: 5)
[00:21:39 -91459.188521] SLOW spr round 3 (radius: 5)
[00:21:58 -91459.187221] SLOW spr round 4 (radius: 10)
[00:22:18 -91459.186566] SLOW spr round 5 (radius: 15)
[00:22:57 -91459.186179] SLOW spr round 6 (radius: 20)
[00:23:35 -91459.185923] SLOW spr round 7 (radius: 25)
[00:24:08 -91459.185743] Model parameter optimization (eps = 0.100000)

[00:24:12] ML tree search #4, logLikelihood: -91459.004295

[00:24:12 -285232.868942] Initial branch length optimization
[00:24:12 -205198.571260] Model parameter optimization (eps = 10.000000)
[00:24:23 -204278.961802] AUTODETECT spr round 1 (radius: 5)
[00:24:33 -156369.422197] AUTODETECT spr round 2 (radius: 10)
[00:24:46 -113222.508295] AUTODETECT spr round 3 (radius: 15)
[00:25:03 -100571.508781] AUTODETECT spr round 4 (radius: 20)
[00:25:22 -100450.055995] AUTODETECT spr round 5 (radius: 25)
[00:25:40 -100445.976334] SPR radius for FAST iterations: 25 (autodetect)
[00:25:40 -100445.976334] Model parameter optimization (eps = 3.000000)
[00:25:51 -100142.515255] FAST spr round 1 (radius: 25)
[00:26:10 -91880.516036] FAST spr round 2 (radius: 25)
[00:26:23 -91505.686482] FAST spr round 3 (radius: 25)
[00:26:34 -91483.373071] FAST spr round 4 (radius: 25)
[00:26:43 -91480.718685] FAST spr round 5 (radius: 25)
[00:26:52 -91480.650117] Model parameter optimization (eps = 1.000000)
[00:26:57 -91477.573912] SLOW spr round 1 (radius: 5)
[00:27:17 -91459.786360] SLOW spr round 2 (radius: 5)
[00:27:36 -91458.273659] SLOW spr round 3 (radius: 5)
[00:27:55 -91458.272175] SLOW spr round 4 (radius: 10)
[00:28:14 -91458.271262] SLOW spr round 5 (radius: 15)
[00:28:54 -91458.270587] SLOW spr round 6 (radius: 20)
[00:29:33 -91458.270080] SLOW spr round 7 (radius: 25)
[00:30:04 -91458.269698] Model parameter optimization (eps = 0.100000)

[00:30:06] ML tree search #5, logLikelihood: -91458.225090

[00:30:06 -279994.300379] Initial branch length optimization
[00:30:07 -202379.180259] Model parameter optimization (eps = 10.000000)
[00:30:23 -201519.333924] AUTODETECT spr round 1 (radius: 5)
[00:30:33 -157313.208241] AUTODETECT spr round 2 (radius: 10)
[00:30:48 -120278.421467] AUTODETECT spr round 3 (radius: 15)
[00:31:06 -99398.061474] AUTODETECT spr round 4 (radius: 20)
[00:31:25 -99300.106787] AUTODETECT spr round 5 (radius: 25)
[00:31:43 -99300.090673] SPR radius for FAST iterations: 20 (autodetect)
[00:31:43 -99300.090673] Model parameter optimization (eps = 3.000000)
[00:31:53 -99065.067398] FAST spr round 1 (radius: 20)
[00:32:09 -92562.208711] FAST spr round 2 (radius: 20)
[00:32:23 -91590.800936] FAST spr round 3 (radius: 20)
[00:32:35 -91489.321940] FAST spr round 4 (radius: 20)
[00:32:44 -91488.952783] FAST spr round 5 (radius: 20)
[00:32:54 -91488.941173] Model parameter optimization (eps = 1.000000)
[00:32:59 -91480.451256] SLOW spr round 1 (radius: 5)
[00:33:19 -91465.082857] SLOW spr round 2 (radius: 5)
[00:33:39 -91462.497549] SLOW spr round 3 (radius: 5)
[00:33:58 -91462.496499] SLOW spr round 4 (radius: 10)
[00:34:18 -91462.495869] SLOW spr round 5 (radius: 15)
[00:34:58 -91462.495425] SLOW spr round 6 (radius: 20)
[00:35:39 -91462.495097] SLOW spr round 7 (radius: 25)
[00:36:16 -91462.494850] Model parameter optimization (eps = 0.100000)

[00:36:19] ML tree search #6, logLikelihood: -91462.323805

[00:36:19 -288416.413278] Initial branch length optimization
[00:36:20 -209632.091677] Model parameter optimization (eps = 10.000000)
[00:36:35 -208702.345235] AUTODETECT spr round 1 (radius: 5)
[00:36:45 -161879.646791] AUTODETECT spr round 2 (radius: 10)
[00:36:59 -116428.754585] AUTODETECT spr round 3 (radius: 15)
[00:37:18 -99682.685553] AUTODETECT spr round 4 (radius: 20)
[00:37:35 -98607.599303] AUTODETECT spr round 5 (radius: 25)
[00:37:50 -98576.096810] SPR radius for FAST iterations: 25 (autodetect)
[00:37:50 -98576.096810] Model parameter optimization (eps = 3.000000)
[00:38:00 -98256.402178] FAST spr round 1 (radius: 25)
[00:38:19 -91932.299922] FAST spr round 2 (radius: 25)
[00:38:34 -91503.999709] FAST spr round 3 (radius: 25)
[00:38:44 -91492.933516] FAST spr round 4 (radius: 25)
[00:38:53 -91492.931101] Model parameter optimization (eps = 1.000000)
[00:38:59 -91487.814110] SLOW spr round 1 (radius: 5)
[00:39:19 -91474.511880] SLOW spr round 2 (radius: 5)
[00:39:37 -91474.416976] SLOW spr round 3 (radius: 10)
[00:39:57 -91473.396850] SLOW spr round 4 (radius: 5)
[00:40:23 -91473.395718] SLOW spr round 5 (radius: 10)
[00:40:50 -91473.394914] SLOW spr round 6 (radius: 15)
[00:41:26 -91473.394315] SLOW spr round 7 (radius: 20)
[00:42:05 -91473.393864] SLOW spr round 8 (radius: 25)
[00:42:36 -91473.393523] Model parameter optimization (eps = 0.100000)

[00:42:38] ML tree search #7, logLikelihood: -91473.316859

[00:42:38 -280552.141533] Initial branch length optimization
[00:42:38 -205784.340340] Model parameter optimization (eps = 10.000000)
[00:42:49 -204857.337322] AUTODETECT spr round 1 (radius: 5)
[00:42:59 -160762.500722] AUTODETECT spr round 2 (radius: 10)
[00:43:12 -117843.609431] AUTODETECT spr round 3 (radius: 15)
[00:43:29 -100217.241348] AUTODETECT spr round 4 (radius: 20)
[00:43:49 -99660.383665] AUTODETECT spr round 5 (radius: 25)
[00:44:08 -99660.285099] SPR radius for FAST iterations: 20 (autodetect)
[00:44:08 -99660.285099] Model parameter optimization (eps = 3.000000)
[00:44:18 -99387.375586] FAST spr round 1 (radius: 20)
[00:44:35 -91713.669360] FAST spr round 2 (radius: 20)
[00:44:48 -91500.971488] FAST spr round 3 (radius: 20)
[00:45:00 -91486.981667] FAST spr round 4 (radius: 20)
[00:45:10 -91484.010585] FAST spr round 5 (radius: 20)
[00:45:19 -91484.008461] Model parameter optimization (eps = 1.000000)
[00:45:24 -91479.037968] SLOW spr round 1 (radius: 5)
[00:45:44 -91462.229373] SLOW spr round 2 (radius: 5)
[00:46:03 -91460.062339] SLOW spr round 3 (radius: 5)
[00:46:22 -91460.059767] SLOW spr round 4 (radius: 10)
[00:46:43 -91460.058755] SLOW spr round 5 (radius: 15)
[00:47:25 -91460.058328] SLOW spr round 6 (radius: 20)
[00:48:05 -91460.058134] SLOW spr round 7 (radius: 25)
[00:48:38 -91460.058035] Model parameter optimization (eps = 0.100000)

[00:48:40] ML tree search #8, logLikelihood: -91460.050906

[00:48:40 -282481.069364] Initial branch length optimization
[00:48:40 -207268.097571] Model parameter optimization (eps = 10.000000)
[00:48:50 -206384.001862] AUTODETECT spr round 1 (radius: 5)
[00:49:00 -151917.887777] AUTODETECT spr round 2 (radius: 10)
[00:49:13 -127853.198374] AUTODETECT spr round 3 (radius: 15)
[00:49:30 -100650.924085] AUTODETECT spr round 4 (radius: 20)
[00:49:50 -99981.128160] AUTODETECT spr round 5 (radius: 25)
[00:50:09 -99917.576885] SPR radius for FAST iterations: 25 (autodetect)
[00:50:09 -99917.576885] Model parameter optimization (eps = 3.000000)
[00:50:20 -99641.197169] FAST spr round 1 (radius: 25)
[00:50:38 -91866.139291] FAST spr round 2 (radius: 25)
[00:50:52 -91513.749639] FAST spr round 3 (radius: 25)
[00:51:03 -91511.738372] FAST spr round 4 (radius: 25)
[00:51:13 -91502.493085] FAST spr round 5 (radius: 25)
[00:51:22 -91500.001539] FAST spr round 6 (radius: 25)
[00:51:31 -91499.997456] Model parameter optimization (eps = 1.000000)
[00:51:37 -91493.439327] SLOW spr round 1 (radius: 5)
[00:51:56 -91463.035590] SLOW spr round 2 (radius: 5)
[00:52:15 -91462.542286] SLOW spr round 3 (radius: 5)
[00:52:33 -91462.541832] SLOW spr round 4 (radius: 10)
[00:52:54 -91462.541643] SLOW spr round 5 (radius: 15)
[00:53:35 -91462.541550] SLOW spr round 6 (radius: 20)
[00:54:16 -91462.541499] SLOW spr round 7 (radius: 25)
[00:54:51 -91462.541468] Model parameter optimization (eps = 0.100000)

[00:54:54] ML tree search #9, logLikelihood: -91462.441631

[00:54:54 -285899.736233] Initial branch length optimization
[00:54:54 -208660.409713] Model parameter optimization (eps = 10.000000)
[00:55:08 -207765.009646] AUTODETECT spr round 1 (radius: 5)
[00:55:18 -148813.834871] AUTODETECT spr round 2 (radius: 10)
[00:55:32 -116895.010699] AUTODETECT spr round 3 (radius: 15)
[00:55:48 -101344.735837] AUTODETECT spr round 4 (radius: 20)
[00:56:06 -101239.623779] AUTODETECT spr round 5 (radius: 25)
[00:56:21 -101220.301551] SPR radius for FAST iterations: 25 (autodetect)
[00:56:21 -101220.301551] Model parameter optimization (eps = 3.000000)
[00:56:33 -100900.781394] FAST spr round 1 (radius: 25)
[00:56:54 -91937.682275] FAST spr round 2 (radius: 25)
[00:57:09 -91492.635708] FAST spr round 3 (radius: 25)
[00:57:19 -91488.912709] FAST spr round 4 (radius: 25)
[00:57:28 -91488.910401] Model parameter optimization (eps = 1.000000)
[00:57:32 -91486.853250] SLOW spr round 1 (radius: 5)
[00:57:53 -91467.940174] SLOW spr round 2 (radius: 5)
[00:58:11 -91464.292126] SLOW spr round 3 (radius: 5)
[00:58:29 -91463.918026] SLOW spr round 4 (radius: 5)
[00:58:47 -91463.905366] SLOW spr round 5 (radius: 10)
[00:59:06 -91463.812687] SLOW spr round 6 (radius: 15)
[00:59:43 -91463.713727] SLOW spr round 7 (radius: 20)
[01:00:19 -91463.641836] SLOW spr round 8 (radius: 25)
[01:00:55 -91463.590121] Model parameter optimization (eps = 0.100000)

[01:00:56] ML tree search #10, logLikelihood: -91463.544280

[01:00:56 -289412.008799] Initial branch length optimization
[01:00:57 -209020.827231] Model parameter optimization (eps = 10.000000)
[01:01:13 -208136.834368] AUTODETECT spr round 1 (radius: 5)
[01:01:23 -144593.464629] AUTODETECT spr round 2 (radius: 10)
[01:01:35 -126046.563938] AUTODETECT spr round 3 (radius: 15)
[01:01:51 -104489.048402] AUTODETECT spr round 4 (radius: 20)
[01:02:07 -98083.690807] AUTODETECT spr round 5 (radius: 25)
[01:02:22 -98083.620861] SPR radius for FAST iterations: 20 (autodetect)
[01:02:22 -98083.620861] Model parameter optimization (eps = 3.000000)
[01:02:34 -97760.084481] FAST spr round 1 (radius: 20)
[01:02:50 -91772.373501] FAST spr round 2 (radius: 20)
[01:03:04 -91500.955501] FAST spr round 3 (radius: 20)
[01:03:15 -91483.936839] FAST spr round 4 (radius: 20)
[01:03:23 -91483.908444] Model parameter optimization (eps = 1.000000)
[01:03:29 -91478.064855] SLOW spr round 1 (radius: 5)
[01:03:48 -91465.033354] SLOW spr round 2 (radius: 5)
[01:04:06 -91462.418743] SLOW spr round 3 (radius: 5)
[01:04:24 -91462.415806] SLOW spr round 4 (radius: 10)
[01:04:43 -91462.414391] SLOW spr round 5 (radius: 15)
[01:05:22 -91462.413639] SLOW spr round 6 (radius: 20)
[01:06:00 -91462.413228] SLOW spr round 7 (radius: 25)
[01:06:31 -91462.412997] Model parameter optimization (eps = 0.100000)

[01:06:34] ML tree search #11, logLikelihood: -91462.303244

[01:06:34 -283111.389006] Initial branch length optimization
[01:06:35 -206398.873223] Model parameter optimization (eps = 10.000000)
[01:06:50 -205468.035882] AUTODETECT spr round 1 (radius: 5)
[01:07:00 -155179.728026] AUTODETECT spr round 2 (radius: 10)
[01:07:12 -130934.219054] AUTODETECT spr round 3 (radius: 15)
[01:07:30 -105958.530417] AUTODETECT spr round 4 (radius: 20)
[01:07:52 -100777.357894] AUTODETECT spr round 5 (radius: 25)
[01:08:12 -100107.502452] SPR radius for FAST iterations: 25 (autodetect)
[01:08:12 -100107.502452] Model parameter optimization (eps = 3.000000)
[01:08:21 -99834.132181] FAST spr round 1 (radius: 25)
[01:08:40 -91995.948683] FAST spr round 2 (radius: 25)
[01:08:51 -91493.732063] FAST spr round 3 (radius: 25)
[01:09:03 -91481.825536] FAST spr round 4 (radius: 25)
[01:09:11 -91480.397473] FAST spr round 5 (radius: 25)
[01:09:20 -91480.394549] Model parameter optimization (eps = 1.000000)
[01:09:26 -91473.228935] SLOW spr round 1 (radius: 5)
[01:09:44 -91469.690528] SLOW spr round 2 (radius: 5)
[01:10:01 -91469.686655] SLOW spr round 3 (radius: 10)
[01:10:20 -91469.685441] SLOW spr round 4 (radius: 15)
[01:10:58 -91469.684636] SLOW spr round 5 (radius: 20)
[01:11:35 -91469.684061] SLOW spr round 6 (radius: 25)
[01:12:06 -91469.683640] Model parameter optimization (eps = 0.100000)

[01:12:08] ML tree search #12, logLikelihood: -91469.667843

[01:12:08 -286615.654802] Initial branch length optimization
[01:12:08 -208061.818735] Model parameter optimization (eps = 10.000000)
[01:12:19 -207187.865531] AUTODETECT spr round 1 (radius: 5)
[01:12:29 -145710.196038] AUTODETECT spr round 2 (radius: 10)
[01:12:41 -122783.739594] AUTODETECT spr round 3 (radius: 15)
[01:12:59 -98793.500223] AUTODETECT spr round 4 (radius: 20)
[01:13:19 -98580.489107] AUTODETECT spr round 5 (radius: 25)
[01:13:37 -98578.746164] SPR radius for FAST iterations: 25 (autodetect)
[01:13:37 -98578.746164] Model parameter optimization (eps = 3.000000)
[01:13:51 -98307.863607] FAST spr round 1 (radius: 25)
[01:14:12 -91588.651027] FAST spr round 2 (radius: 25)
[01:14:23 -91475.151021] FAST spr round 3 (radius: 25)
[01:14:33 -91472.652479] FAST spr round 4 (radius: 25)
[01:14:41 -91472.652115] Model parameter optimization (eps = 1.000000)
[01:14:47 -91468.064988] SLOW spr round 1 (radius: 5)
[01:15:06 -91463.051839] SLOW spr round 2 (radius: 5)
[01:15:23 -91462.520046] SLOW spr round 3 (radius: 5)
[01:15:41 -91462.518365] SLOW spr round 4 (radius: 10)
[01:16:01 -91462.518098] SLOW spr round 5 (radius: 15)
[01:16:39 -91462.518028] SLOW spr round 6 (radius: 20)
[01:17:17 -91462.517997] SLOW spr round 7 (radius: 25)
[01:17:50 -91462.517979] Model parameter optimization (eps = 0.100000)

[01:17:52] ML tree search #13, logLikelihood: -91462.423188

[01:17:52 -286645.079102] Initial branch length optimization
[01:17:52 -208689.867214] Model parameter optimization (eps = 10.000000)
[01:18:08 -207742.633650] AUTODETECT spr round 1 (radius: 5)
[01:18:18 -160089.136826] AUTODETECT spr round 2 (radius: 10)
[01:18:30 -134454.273850] AUTODETECT spr round 3 (radius: 15)
[01:18:46 -106803.533451] AUTODETECT spr round 4 (radius: 20)
[01:19:07 -102936.012392] AUTODETECT spr round 5 (radius: 25)
[01:19:27 -102918.709649] SPR radius for FAST iterations: 25 (autodetect)
[01:19:27 -102918.709649] Model parameter optimization (eps = 3.000000)
[01:19:36 -102659.472171] FAST spr round 1 (radius: 25)
[01:19:55 -92577.990859] FAST spr round 2 (radius: 25)
[01:20:10 -91521.415903] FAST spr round 3 (radius: 25)
[01:20:21 -91486.886316] FAST spr round 4 (radius: 25)
[01:20:29 -91486.884623] Model parameter optimization (eps = 1.000000)
[01:20:36 -91469.703131] SLOW spr round 1 (radius: 5)
[01:20:56 -91459.383496] SLOW spr round 2 (radius: 5)
[01:21:14 -91459.380441] SLOW spr round 3 (radius: 10)
[01:21:33 -91459.379066] SLOW spr round 4 (radius: 15)
[01:22:12 -91459.378098] SLOW spr round 5 (radius: 20)
[01:22:49 -91459.377379] SLOW spr round 6 (radius: 25)
[01:23:19 -91459.376829] Model parameter optimization (eps = 0.100000)

[01:23:20] ML tree search #14, logLikelihood: -91459.365304

[01:23:20 -286848.790565] Initial branch length optimization
[01:23:20 -210064.075823] Model parameter optimization (eps = 10.000000)
[01:23:34 -209143.984772] AUTODETECT spr round 1 (radius: 5)
[01:23:44 -162371.319295] AUTODETECT spr round 2 (radius: 10)
[01:23:57 -131962.576760] AUTODETECT spr round 3 (radius: 15)
[01:24:14 -103508.933885] AUTODETECT spr round 4 (radius: 20)
[01:24:34 -100019.712961] AUTODETECT spr round 5 (radius: 25)
[01:24:54 -100016.776720] SPR radius for FAST iterations: 25 (autodetect)
[01:24:54 -100016.776720] Model parameter optimization (eps = 3.000000)
[01:25:03 -99752.836239] FAST spr round 1 (radius: 25)
[01:25:19 -91845.515745] FAST spr round 2 (radius: 25)
[01:25:30 -91477.672016] FAST spr round 3 (radius: 25)
[01:25:40 -91474.929780] FAST spr round 4 (radius: 25)
[01:25:49 -91472.897165] FAST spr round 5 (radius: 25)
[01:25:57 -91472.896432] Model parameter optimization (eps = 1.000000)
[01:26:04 -91469.277751] SLOW spr round 1 (radius: 5)
[01:26:22 -91461.775000] SLOW spr round 2 (radius: 5)
[01:26:40 -91461.699399] SLOW spr round 3 (radius: 10)
[01:26:59 -91461.699187] SLOW spr round 4 (radius: 15)
[01:27:38 -91461.699075] SLOW spr round 5 (radius: 20)
[01:28:14 -91461.699008] SLOW spr round 6 (radius: 25)
[01:28:46 -91461.698965] Model parameter optimization (eps = 0.100000)

[01:28:47] ML tree search #15, logLikelihood: -91461.697716

[01:28:47 -283969.196454] Initial branch length optimization
[01:28:48 -204722.653393] Model parameter optimization (eps = 10.000000)
[01:29:00 -203859.240712] AUTODETECT spr round 1 (radius: 5)
[01:29:09 -152235.651393] AUTODETECT spr round 2 (radius: 10)
[01:29:22 -111497.924985] AUTODETECT spr round 3 (radius: 15)
[01:29:37 -103484.756648] AUTODETECT spr round 4 (radius: 20)
[01:29:53 -102538.099125] AUTODETECT spr round 5 (radius: 25)
[01:30:05 -102538.061007] SPR radius for FAST iterations: 20 (autodetect)
[01:30:05 -102538.061007] Model parameter optimization (eps = 3.000000)
[01:30:16 -102217.971102] FAST spr round 1 (radius: 20)
[01:30:30 -91783.775284] FAST spr round 2 (radius: 20)
[01:30:43 -91494.257090] FAST spr round 3 (radius: 20)
[01:30:53 -91490.557451] FAST spr round 4 (radius: 20)
[01:31:03 -91487.263627] FAST spr round 5 (radius: 20)
[01:31:11 -91487.263030] Model parameter optimization (eps = 1.000000)
[01:31:16 -91481.675110] SLOW spr round 1 (radius: 5)
[01:31:35 -91462.793064] SLOW spr round 2 (radius: 5)
[01:31:54 -91459.824761] SLOW spr round 3 (radius: 5)
[01:32:13 -91458.657793] SLOW spr round 4 (radius: 5)
[01:32:31 -91458.656657] SLOW spr round 5 (radius: 10)
[01:32:50 -91458.656201] SLOW spr round 6 (radius: 15)
[01:33:26 -91458.655991] SLOW spr round 7 (radius: 20)
[01:34:04 -91458.655886] SLOW spr round 8 (radius: 25)
[01:34:34 -91458.655829] Model parameter optimization (eps = 0.100000)

[01:34:37] ML tree search #16, logLikelihood: -91458.457575

[01:34:37 -285166.591833] Initial branch length optimization
[01:34:37 -203620.530644] Model parameter optimization (eps = 10.000000)
[01:34:47 -202742.079026] AUTODETECT spr round 1 (radius: 5)
[01:34:56 -156175.073628] AUTODETECT spr round 2 (radius: 10)
[01:35:10 -115986.963935] AUTODETECT spr round 3 (radius: 15)
[01:35:26 -99962.149123] AUTODETECT spr round 4 (radius: 20)
[01:35:43 -99518.856733] AUTODETECT spr round 5 (radius: 25)
[01:35:59 -99375.677610] SPR radius for FAST iterations: 25 (autodetect)
[01:35:59 -99375.677610] Model parameter optimization (eps = 3.000000)
[01:36:11 -99128.552368] FAST spr round 1 (radius: 25)
[01:36:31 -91904.137228] FAST spr round 2 (radius: 25)
[01:36:48 -91495.595994] FAST spr round 3 (radius: 25)
[01:37:00 -91479.777883] FAST spr round 4 (radius: 25)
[01:37:09 -91477.646402] FAST spr round 5 (radius: 25)
[01:37:18 -91477.646296] Model parameter optimization (eps = 1.000000)
[01:37:23 -91468.516940] SLOW spr round 1 (radius: 5)
[01:37:42 -91465.340854] SLOW spr round 2 (radius: 5)
[01:37:59 -91464.843242] SLOW spr round 3 (radius: 5)
[01:38:17 -91464.840675] SLOW spr round 4 (radius: 10)
[01:38:36 -91464.839618] SLOW spr round 5 (radius: 15)
[01:39:12 -91464.839118] SLOW spr round 6 (radius: 20)
[01:39:49 -91464.838852] SLOW spr round 7 (radius: 25)
[01:40:21 -91464.838696] Model parameter optimization (eps = 0.100000)

[01:40:23] ML tree search #17, logLikelihood: -91464.770747

[01:40:23 -287266.836959] Initial branch length optimization
[01:40:24 -207839.496762] Model parameter optimization (eps = 10.000000)
[01:40:35 -206956.166195] AUTODETECT spr round 1 (radius: 5)
[01:40:44 -159527.121534] AUTODETECT spr round 2 (radius: 10)
[01:40:57 -127579.689154] AUTODETECT spr round 3 (radius: 15)
[01:41:13 -99362.536729] AUTODETECT spr round 4 (radius: 20)
[01:41:32 -99316.889248] AUTODETECT spr round 5 (radius: 25)
[01:41:49 -99316.819089] SPR radius for FAST iterations: 20 (autodetect)
[01:41:49 -99316.819089] Model parameter optimization (eps = 3.000000)
[01:42:00 -99005.237454] FAST spr round 1 (radius: 20)
[01:42:17 -91618.784006] FAST spr round 2 (radius: 20)
[01:42:30 -91510.541074] FAST spr round 3 (radius: 20)
[01:42:40 -91502.574796] FAST spr round 4 (radius: 20)
[01:42:50 -91491.711946] FAST spr round 5 (radius: 20)
[01:42:59 -91489.129076] FAST spr round 6 (radius: 20)
[01:43:07 -91489.128911] Model parameter optimization (eps = 1.000000)
[01:43:14 -91485.696287] SLOW spr round 1 (radius: 5)
[01:43:33 -91468.873826] SLOW spr round 2 (radius: 5)
[01:43:51 -91468.363286] SLOW spr round 3 (radius: 5)
[01:44:08 -91468.361874] SLOW spr round 4 (radius: 10)
[01:44:27 -91468.361099] SLOW spr round 5 (radius: 15)
[01:45:01 -91468.360660] SLOW spr round 6 (radius: 20)
[01:45:36 -91468.360408] SLOW spr round 7 (radius: 25)
[01:46:09 -91468.360261] Model parameter optimization (eps = 0.100000)

[01:46:11] ML tree search #18, logLikelihood: -91468.286633

[01:46:11 -284775.425954] Initial branch length optimization
[01:46:12 -207151.507797] Model parameter optimization (eps = 10.000000)
[01:46:23 -206244.283029] AUTODETECT spr round 1 (radius: 5)
[01:46:32 -149910.202084] AUTODETECT spr round 2 (radius: 10)
[01:46:45 -110131.616667] AUTODETECT spr round 3 (radius: 15)
[01:47:00 -100624.929084] AUTODETECT spr round 4 (radius: 20)
[01:47:17 -99469.065465] AUTODETECT spr round 5 (radius: 25)
[01:47:31 -99460.511953] SPR radius for FAST iterations: 25 (autodetect)
[01:47:31 -99460.511953] Model parameter optimization (eps = 3.000000)
[01:47:42 -99144.862767] FAST spr round 1 (radius: 25)
[01:48:01 -92159.520922] FAST spr round 2 (radius: 25)
[01:48:16 -91541.531316] FAST spr round 3 (radius: 25)
[01:48:27 -91500.963688] FAST spr round 4 (radius: 25)
[01:48:37 -91494.387201] FAST spr round 5 (radius: 25)
[01:48:46 -91494.079419] FAST spr round 6 (radius: 25)
[01:48:54 -91494.077187] Model parameter optimization (eps = 1.000000)
[01:49:00 -91483.647860] SLOW spr round 1 (radius: 5)
[01:49:18 -91477.362736] SLOW spr round 2 (radius: 5)
[01:49:36 -91477.334568] SLOW spr round 3 (radius: 10)
[01:49:54 -91477.332480] SLOW spr round 4 (radius: 15)
[01:50:33 -91477.331687] SLOW spr round 5 (radius: 20)
[01:51:10 -91477.331332] SLOW spr round 6 (radius: 25)
[01:51:43 -91477.331142] Model parameter optimization (eps = 0.100000)

[01:51:45] ML tree search #19, logLikelihood: -91477.302202

[01:51:45 -288636.189859] Initial branch length optimization
[01:51:46 -207627.274953] Model parameter optimization (eps = 10.000000)
[01:52:01 -206684.270666] AUTODETECT spr round 1 (radius: 5)
[01:52:10 -152030.042001] AUTODETECT spr round 2 (radius: 10)
[01:52:25 -104428.257596] AUTODETECT spr round 3 (radius: 15)
[01:52:41 -97903.992402] AUTODETECT spr round 4 (radius: 20)
[01:52:59 -97846.052144] AUTODETECT spr round 5 (radius: 25)
[01:53:18 -97845.982160] SPR radius for FAST iterations: 20 (autodetect)
[01:53:18 -97845.982160] Model parameter optimization (eps = 3.000000)
[01:53:28 -97566.153122] FAST spr round 1 (radius: 20)
[01:53:44 -91927.898863] FAST spr round 2 (radius: 20)
[01:53:57 -91503.233415] FAST spr round 3 (radius: 20)
[01:54:07 -91489.342860] FAST spr round 4 (radius: 20)
[01:54:16 -91489.340836] Model parameter optimization (eps = 1.000000)
[01:54:22 -91481.771777] SLOW spr round 1 (radius: 5)
[01:54:40 -91473.208126] SLOW spr round 2 (radius: 5)
[01:54:59 -91472.324885] SLOW spr round 3 (radius: 5)
[01:55:17 -91472.324084] SLOW spr round 4 (radius: 10)
[01:55:37 -91472.323929] SLOW spr round 5 (radius: 15)
[01:56:16 -91472.323828] SLOW spr round 6 (radius: 20)
[01:56:54 -91472.323749] SLOW spr round 7 (radius: 25)
[01:57:25 -91472.323679] Model parameter optimization (eps = 0.100000)

[01:57:27] ML tree search #20, logLikelihood: -91472.225307


Optimized model parameters:

   Partition 0: noname
   Rate heterogeneity: FREE (4 cats, mean),  weights&rates: (0.307979,0.510265) (0.282539,0.686249) (0.289254,1.151285) (0.120227,2.627881) 
   Base frequencies (model): 
M0: 0.147383 0.017579 0.058208 0.017707 0.026331 0.041582 0.017494 0.027859 0.011849 0.076971 0.147823 0.019535 0.037132 0.029940 0.008059 0.088179 0.089653 0.006477 0.032308 0.097931 
M1: 0.063139 0.066357 0.011586 0.066571 0.010800 0.009276 0.053984 0.146986 0.034214 0.088822 0.098196 0.032390 0.021263 0.072697 0.016761 0.020711 0.020797 0.025463 0.045615 0.094372 
M2: 0.062457 0.066826 0.049332 0.065270 0.006513 0.041231 0.058965 0.080852 0.028024 0.037024 0.075925 0.064131 0.019620 0.028710 0.104579 0.056388 0.062027 0.008241 0.033124 0.050760 
M3: 0.106471 0.074171 0.044513 0.096390 0.002148 0.066733 0.158908 0.037625 0.020691 0.014608 0.028797 0.105352 0.007864 0.007477 0.083595 0.055726 0.047711 0.003975 0.010088 0.027159 
   Substitution rates (model): 
M 0: 0.295719 0.067388 0.253712 1.029289 0.107964 0.514644 10.868848 0.380498 0.084223 0.086976 0.188789 0.286389 0.155567 1.671061 2.132922 0.529591 0.115551 0.102453 0.916683 0.448317 0.457483 0.576016 1.741924 0.736017 0.704334 5.658311 0.123387 0.221777 93.433377 0.382175 0.235965 6.535048 0.525521 0.303537 0.641259 0.289466 0.102065 2.358429 0.251987 0.216561 0.503084 0.435271 4.873453 0.090748 0.033310 0.746537 0.128905 0.127321 0.904011 0.939733 0.435450 0.046646 0.262076 0.043986 0.189008 0.599450 109.901504 1.070052 5.229858 0.052764 0.021407 0.621146 0.081091 0.205164 5.164456 0.747330 0.308078 0.260889 0.185083 0.080708 0.029955 0.084794 1.862626 0.553477 0.151733 0.230320 0.096955 0.352526 0.590018 0.386853 1.559564 0.606648 0.587531 0.592318 0.885230 4.117654 0.246260 6.508329 0.054187 0.195703 1.669092 0.810168 0.066081 2.437439 0.165666 0.106333 0.093417 0.035149 0.072549 1.202023 1.634845 0.060194 0.069359 2.448827 0.232297 0.064822 3.537387 0.435384 0.290413 0.280695 0.105999 0.206603 0.404968 0.048984 0.069963 0.256662 0.228519 0.241077 4.320442 3.656545 0.290216 0.307466 0.096556 0.306067 0.204296 0.504221 1.991533 0.655465 6.799829 11.291065 0.961142 0.448965 6.227274 20.304886 0.205944 1.495537 0.091940 1.994320 0.754940 0.170343 0.050315 0.372166 0.206332 0.097050 5.381403 0.122332 3.256485 2.261319 0.848067 0.064441 0.102493 0.459041 0.133091 0.561215 0.457430 0.163849 5.260446 0.360946 0.389413 0.033291 0.115301 0.112593 1.559944 0.426508 0.132547 0.498634 0.559069 0.264728 0.693307 0.438856 0.306683 0.109129 18.392863 66.647302 0.400021 4.586081 2.099355 0.411347 0.476350 0.584622 3.634276 0.101797 0.148995 0.089177 0.034710 0.063603 0.755865 20.561407 0.133790 0.154902 
M 1: 0.066142 0.590377 0.069930 9.850951 1.101363 0.150375 0.568586 0.051668 0.127170 0.292429 0.071458 1.218562 0.075144 7.169085 30.139501 13.461692 0.021372 0.045779 4.270235 0.468325 0.013688 0.302287 1.353957 0.028386 0.037750 0.262130 0.016923 0.064289 0.855973 0.079621 0.011169 0.161937 0.276530 0.161053 0.081472 0.036742 0.030342 2.851667 3.932151 8.159169 0.219934 0.421974 2.468752 0.344765 0.210724 1.172204 0.763553 0.082464 0.726566 11.149790 4.782635 0.058046 0.498072 0.258487 0.146882 0.249672 0.560142 0.046719 0.106259 0.003656 0.004200 0.014189 0.009876 0.002656 0.040244 0.267322 0.053740 0.006597 0.027639 0.012745 0.582670 0.005035 0.275844 0.098208 0.445038 1.217010 0.033969 1.988516 0.681161 0.825960 18.762977 11.949233 0.286794 0.534219 4.336817 3.054085 0.129551 4.210126 0.165753 1.088704 1.889645 3.344809 0.111063 2.067758 3.547017 2.466507 0.188236 0.203493 0.281953 0.037250 0.029788 0.008541 0.014768 0.125869 0.056702 0.004186 0.110993 0.201148 0.139705 0.009201 0.012095 0.043812 0.013513 0.002533 0.005848 0.031390 0.021612 0.004854 0.129497 0.976631 0.053397 0.019475 0.004964 0.015539 0.031779 0.064558 0.065585 0.079927 0.095591 0.196886 0.408834 0.126088 0.037226 0.452302 0.016212 7.278994 0.029917 7.918203 0.450964 0.169797 0.104288 1.578530 0.015909 0.094365 16.179952 0.042762 14.799537 1.506485 0.637893 0.123793 0.641351 0.154810 0.140750 3.416059 0.259400 0.009457 0.090576 0.292108 0.297913 0.017172 0.021976 0.032578 1.375871 0.457399 0.598048 4.418398 0.239749 0.168432 2.950318 0.143327 0.328689 0.125011 0.562720 1.414883 0.227807 3.478333 2.984862 0.061299 0.077470 1.050562 13.974326 0.154326 0.224675 0.112000 0.060703 0.123480 5.294490 0.447011 0.033381 0.045528 
M 2: 0.733336 0.558955 0.503360 4.149599 1.415369 1.367574 1.263002 0.994098 0.517204 0.775054 0.763094 1.890137 0.540460 0.200122 4.972745 1.825593 0.450842 0.526135 3.839269 0.597671 0.058964 2.863355 2.872594 0.258365 0.366868 2.578946 0.358350 0.672023 5.349861 0.691594 0.063347 0.032875 0.821562 0.580847 0.661866 0.265730 0.395134 5.581680 1.279881 1.335650 0.397108 1.840061 5.739035 0.284730 0.109781 1.612642 0.466979 0.141582 0.019509 4.670980 1.967383 0.088064 0.581928 0.145401 0.225860 0.434096 2.292917 1.024707 0.821921 0.027824 0.021443 0.088850 0.060820 0.018288 0.042687 1.199607 0.420710 0.037642 0.141233 0.090101 1.043232 0.209978 0.823594 3.039380 1.463390 1.983693 0.397640 2.831098 4.102068 0.059723 5.901348 2.034980 2.600668 5.413080 4.193725 4.534772 0.377181 4.877840 0.370939 1.298542 3.509873 2.646440 0.087872 0.072299 1.139018 0.864479 0.390688 0.322761 0.625409 0.496780 0.532488 0.232460 0.169219 0.755219 0.379926 0.020447 0.023282 0.503875 0.577513 0.109318 0.153776 0.696533 0.398817 0.008940 0.043707 0.436013 0.087640 0.064863 0.036426 1.673207 0.124068 0.218118 0.039217 0.104335 0.349195 0.838324 0.888693 0.488389 1.385133 0.050226 0.962470 0.502294 1.065585 8.351808 0.377304 5.102837 0.561690 7.010411 3.054968 0.039318 0.204155 2.653232 0.564368 0.854294 15.559906 0.401070 8.929538 5.525874 0.067505 0.273372 0.437116 1.927515 0.940458 2.508169 1.357738 0.043394 0.023126 0.567639 1.048288 0.120994 0.180650 0.449074 3.135353 0.012695 0.570771 2.319555 1.856122 0.975427 3.404087 0.015631 0.458799 0.151684 4.154750 11.429924 1.457957 0.233109 0.077004 0.011074 0.026268 0.052132 8.113282 0.377578 0.429221 0.260296 0.222293 0.273138 2.903836 4.731579 0.564762 0.681215 
M 3: 0.658412 0.566269 0.854111 0.884454 1.309554 1.272639 1.874713 0.552007 0.227683 0.581512 0.695190 0.967985 0.344015 0.978992 3.427163 2.333253 0.154701 0.221089 2.088785 0.540749 0.058015 5.851132 2.294145 0.182966 0.684164 3.192521 0.528161 1.128882 3.010922 1.012866 0.227296 0.156635 0.878405 0.802754 0.830884 0.431617 0.456530 3.060574 1.279257 1.438430 0.431464 2.075952 4.840271 0.644656 0.266076 2.084975 0.720060 0.291854 0.028961 4.071574 2.258357 0.073037 1.238426 0.199728 0.160296 0.482619 2.992763 1.296206 0.841829 0.031467 0.048542 0.132774 0.133055 0.056045 0.209188 0.925172 0.360522 0.094591 0.313945 0.118104 0.992259 0.086318 2.149634 5.103188 3.775817 3.954021 0.190734 1.776095 4.495841 0.264277 7.063879 2.221150 3.017954 8.558815 4.310199 2.130054 0.571406 4.137385 0.437589 2.071689 2.498630 1.763546 0.116381 0.296578 1.033710 1.283423 0.312579 0.305772 0.681277 0.507160 0.351381 0.189152 0.217780 0.767361 0.278392 0.092075 0.177263 0.451893 0.653836 0.074620 0.181992 0.752277 0.679853 0.025780 0.082005 0.326441 0.343977 0.195877 0.217424 3.057583 0.377558 0.401252 0.072258 0.241015 0.665865 1.266791 0.680174 0.717301 4.001286 0.362942 1.189259 0.964545 1.350568 12.869737 0.531100 8.904999 0.652629 10.091413 2.671718 0.086367 0.359932 4.797423 0.336801 1.021885 23.029406 0.440178 14.013035 5.069337 0.539010 0.742569 0.780580 1.331875 1.531589 4.414850 1.082703 0.091278 0.172734 0.693405 1.422571 0.068958 0.163829 0.481711 4.643214 0.121821 0.584083 4.216178 1.677263 1.575754 5.046403 0.161015 1.531223 0.599244 5.832025 33.873091 1.914768 1.287474 0.444362 0.076328 0.079916 0.466823 5.231362 0.548763 0.831890 0.382271 0.208791 0.307846 3.717971 5.910440 0.282540 0.964421 


Final LogLikelihood: -91458.225090

AIC score: 183822.450181 / AICc score: 184294.152016 / BIC score: 186173.484924
Free parameters (model + branch lengths): 453

WARNING: Best ML tree contains 26 near-zero branches!

Best ML tree with collapsed near-zero branches saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.bestTreeCollapsed
Best ML tree saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.bestTree
All ML trees saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.mlTrees
Optimized model saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.bestModel

Execution log saved to: /truba/home/emrah/WORKFOLDER/PROD/300621_run/phylogeny-snakemake/results/Q9ULK4/3_mltree/Q9ULK4.raxml.log

Analysis started: 01-Jul-2021 15:05:51 / finished: 01-Jul-2021 17:03:18

Elapsed time: 7047.522 seconds

Consumed energy: 680.071 Wh (= 3 km in an electric car, or 17 km with an e-scooter!)